Chris Wellisz profiles MIT’s Amy Finkelstein, who tests economic models with large data sets
PHOTO: PORTER GIFFORD
Ever since she produced a report on elephants in the first grade, Amy Finkelstein knew she would be a scholar like her parents, both PhD biologists. But it wasn’t until her senior year at Harvard College that she chose economics.
Majoring in political science, she decided to take a course in applied microeconomics. It was 1994, and the topics reflected some of the contentious issues of the day in the United States, including how cash welfare payments affected labor force participation and whether people moved around the country in search of more generous welfare benefits.
“That was a totally transformative experience for me,” Finkelstein recalls. “It opened my eyes to the idea that one could use data to inform what had otherwise seemed like ideological debates.”
In the years since, Finkelstein, who now teaches at the Massachusetts Institute of Technology (MIT), has established herself among the country’s preeminent health economists. In a series of groundbreaking studies, she delved into the mechanics of an industry that accounts for 18 percent of US gross domestic product and has been at the center of ferce debates over the government’s role in providing health insurance. Her work has earned her the MacArthur Fellowship and the John Bates Clark Medal, awarded every year by the American Economic Association to the American economist under 40 judged to have made the biggest contribution to the field.
Finkelstein’s extensive body of work ranges across a wide variety of issues, large and small, from estimating the welfare benefits of alternative social insurance programs to the effectiveness of mammogram screening. The common thread: using large data sets to test economic models—and arriving at conclusions that often challenge conventional wisdom.
“What I love about economics is the models and frameworks—the lens it gives you for how to think about social policy problems,” she says. “But I’m not a theorist, and at the end of the day what I like to do is take those models and see how they work in the real world and what the quantitative implications are.”
Finkelstein is a torchbearer for what fellow MIT economist and 2021 Nobel laureate Joshua Angrist has called the “credibility revolution” in empirical economics, which focuses on designing studies that seek to replicate some of the certainty of experiments in the natural sciences.
“That approach has percolated widely into many fields in economics,” says MIT’s James Poterba, who was one of Finkelstein’s thesis advisors. “Amy has been very influential in pushing that forward in the field of health economics.”
Unusually for someone with comparatively little economics training, she won a Marshall Scholarship to study for a master’s degree in economics at the University of Oxford. But the technical nature of the coursework—which seemed to have little relevance to solving real-world problems—left her uncertain about pursuing a doctorate.